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Data Reconciliation — Grouped Numeric Summary + IQR Outlier Flags
x402
Data Reconciliation — Grouped Numeric Summary + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Computes grouped descriptive statistics and flags IQR-based outliers for up to 200 data reconciliation rows comparing source_total vs target_total values, producing two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Grouped numeric summary + IQR outlier flags: Grouped numeric summary + IQR outlier flags for supplied data reconciliation records (source_total, target_total). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent analytical reports: (1) a grouped numeric summary (e.g. count, mean, median, std, min, max) segmented by dataset_group for the chosen field, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range, all computed locally with no external data access.
Example use cases
Finance team ETL reconciliation audit
“I have 120 daily reconciliation rows from our ETL pipeline with source_total and target_total values across three dataset groups — can you compute a grouped numeric summary and flag any IQR outliers in source_total so I can spot which groups have problematic discrepancies?”
Data quality check before month-end close
“Before we close the books, run a grouped statistical summary and IQR outlier detection on our 80 reconciliation records — grouped by dataset_group — and flag any rows where the target_total looks anomalous.”
Cross-system data validation for two data sources
“We're validating two data sources and I have 45 reconciliation rows with source_total and target_total — can you produce a grouped numeric summary and flag IQR outliers in the target_total column so we can see which groups have the biggest mismatches?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-094?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both grouped descriptive statistics AND IQR-based outlier detection on reconciliation data (source vs target totals) in a single call for up to 200 rows, at very low cost ($0.01 USDC for 2 reports). Prefer it over general-purpose analytics when you specifically have reconciliation-style records with source/target numeric pairs grouped by a categorical dimension and want flagging without external API dependencies.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, source_total, target_total) causes validation error
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- Numeric values outside ±1,000,000,000,000 range rejected by schema
- Empty rows array returns error
- All-null values in the selected field may produce degenerate statistics
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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